IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v200y2022icp303-319.html
   My bibliography  Save this article

Boosting the power grid resilience under typhoon disasters by coordinated scheduling of wind energy and conventional generators

Author

Listed:
  • Zhang, Heng
  • Zhang, Shenxi
  • Cheng, Haozhong
  • Li, Zheng
  • Gu, Qingfa
  • Tian, Xueqin

Abstract

Typhoon poses a significant challenge to the reliable and safe operation of power grids. A novel priority-load based preventive scheduling method that considers conventional generators and wind power is proposed to fully exploit the potential of wind power for resilience enhancement. First, the wind speed variation rule in different positions of the typhoon wind speed field is studied according to the characteristics of typhoon. Second, considering the influence of strong wind on the failure rates of transmission lines and tie-lines connecting the power sources and the main grid, the vulnerability curve is used to establish the fault model of lines during typhoon disasters. Third, the utility function of typhoon disaster is represented by the S-type curve, and satisfaction for typhoon resistance (SFTR) index is defined as the objective of coordinated scheduling model. The results show that SFTR can be increased by a factor of 27.9% by exploiting the wind power potential. Compared with the load shedding based method, the priority-load based method proposed in this paper can improve SFTR by 47.6% at most from the perspective of improving the capacity of satisfying important loads to enhance system resilience.

Suggested Citation

  • Zhang, Heng & Zhang, Shenxi & Cheng, Haozhong & Li, Zheng & Gu, Qingfa & Tian, Xueqin, 2022. "Boosting the power grid resilience under typhoon disasters by coordinated scheduling of wind energy and conventional generators," Renewable Energy, Elsevier, vol. 200(C), pages 303-319.
    • Handle: RePEc:eee:renene:v:200:y:2022:i:c:p:303-319
    DOI: 10.1016/j.renene.2022.10.004
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148122014975
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2022.10.004?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Zhang, Dongdong & Li, Chunjiao & Goh, Hui Hwang & Ahmad, Tanveer & Zhu, Hongyu & Liu, Hui & Wu, Thomas, 2022. "A comprehensive overview of modeling approaches and optimal control strategies for cyber-physical resilience in power systems," Renewable Energy, Elsevier, vol. 189(C), pages 1383-1406.
    2. Yadav, Monika & Pal, Nitai & Saini, Devender Kumar, 2021. "Resilient electrical distribution grid planning against seismic waves using distributed energy resources and sectionalizers: An Indian's urban grid case study," Renewable Energy, Elsevier, vol. 178(C), pages 241-259.
    3. Tao, Tianyou & Shi, Peng & Wang, Hao, 2020. "Spectral modelling of typhoon winds considering nexus between longitudinal and lateral components," Renewable Energy, Elsevier, vol. 162(C), pages 2019-2030.
    4. Lin, Yanling & Bie, Zhaohong, 2018. "Tri-level optimal hardening plan for a resilient distribution system considering reconfiguration and DG islanding," Applied Energy, Elsevier, vol. 210(C), pages 1266-1279.
    5. Her, Chong & Sambor, Daniel J. & Whitney, Erin & Wies, Richard, 2021. "Novel wind resource assessment and demand flexibility analysis for community resilience: A remote microgrid case study," Renewable Energy, Elsevier, vol. 179(C), pages 1472-1486.
    6. Devkota, Laxmi P. & Bhattarai, Utsav & Khatri, Pawan & Marahatta, Suresh & Shrestha, Dibesh, 2022. "Resilience of hydropower plants to flow variation through the concept of flow elasticity of power: Theoretical development," Renewable Energy, Elsevier, vol. 184(C), pages 920-932.
    7. Gilani, Mohammad Amin & Kazemi, Ahad & Ghasemi, Mostafa, 2020. "Distribution system resilience enhancement by microgrid formation considering distributed energy resources," Energy, Elsevier, vol. 191(C).
    8. Pantua, Conrad Allan Jay & Calautit, John Kaiser & Wu, Yupeng, 2020. "A fluid-structure interaction (FSI) and energy generation modelling for roof mounted renewable energy installations in buildings for extreme weather and typhoon resilience," Renewable Energy, Elsevier, vol. 160(C), pages 770-787.
    9. Bao, Minglei & Ding, Yi & Sang, Maosheng & Li, Daqing & Shao, Changzheng & Yan, Jinyue, 2020. "Modeling and evaluating nodal resilience of multi-energy systems under windstorms," Applied Energy, Elsevier, vol. 270(C).
    10. Mehrjerdi, Hasan & Hemmati, Reza, 2020. "Coordination of vehicle-to-home and renewable capacity resources for energy management in resilience and self-healing building," Renewable Energy, Elsevier, vol. 146(C), pages 568-579.
    11. Aldarajee, Ammar H.M. & Hosseinian, Seyed H. & Vahidi, Behrooz, 2020. "A secure tri-level planner-disaster-risk-averse replanner model for enhancing the resilience of energy systems," Energy, Elsevier, vol. 204(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Wu, Wenjie & Hou, Hui & Zhu, Shaohua & Liu, Qin & Wei, Ruizeng & He, Huan & Wang, Lei & Luo, Yingting, 2024. "An intelligent power grid emergency allocation technology considering secondary disaster and public opinion under typhoon disaster," Applied Energy, Elsevier, vol. 353(PA).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wang, Chong & Ju, Ping & Wu, Feng & Pan, Xueping & Wang, Zhaoyu, 2022. "A systematic review on power system resilience from the perspective of generation, network, and load," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    2. da Silva, Fellipe Sartori & Matelli, José Alexandre, 2021. "Resilience in cogeneration systems: Metrics for evaluation and influence of design aspects," Reliability Engineering and System Safety, Elsevier, vol. 212(C).
    3. Shang, Ce & Lin, Teng & Li, Canbing & Wang, Keyou & Ai, Qian, 2021. "Joining resilience and reliability evaluation against both weather and ageing causes," Renewable and Sustainable Energy Reviews, Elsevier, vol. 152(C).
    4. Sun, Qirun & Wu, Zhi & Ma, Zhoujun & Gu, Wei & Zhang, Xiao-Ping & Lu, Yuping & Liu, Pengxiang, 2022. "Resilience enhancement strategy for multi-energy systems considering multi-stage recovery process and multi-energy coordination," Energy, Elsevier, vol. 241(C).
    5. Xu, Jiuping & Tian, Yalou & Wang, Fengjuan & Yang, Guocan & Zhao, Chuandang, 2024. "Resilience-economy-environment equilibrium based configuration interaction approach towards distributed energy system in energy intensive industry parks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 191(C).
    6. Zhao, Shihao & Li, Kang & Yin, Mingjia & Yu, James & Yang, Zhile & Li, Yihuan, 2024. "Transportable energy storage assisted post-disaster restoration of distribution networks with renewable generations," Energy, Elsevier, vol. 295(C).
    7. Li, Zhengmao & Xu, Yan & Wang, Peng & Xiao, Gaoxi, 2023. "Coordinated preparation and recovery of a post-disaster Multi-energy distribution system considering thermal inertia and diverse uncertainties," Applied Energy, Elsevier, vol. 336(C).
    8. Ren, Hongbo & Jiang, Zipei & Wu, Qiong & Li, Qifen & Yang, Yongwen, 2022. "Integrated optimization of a regional integrated energy system with thermal energy storage considering both resilience and reliability," Energy, Elsevier, vol. 261(PB).
    9. Fu, Wei & Xie, Haipeng & Zhu, Hao & Wang, Hefeng & Jiang, Lizhou & Chen, Chen & Bie, Zhaohong, 2023. "Coordinated post-disaster restoration for resilient urban distribution systems: A hybrid quantum-classical approach," Energy, Elsevier, vol. 284(C).
    10. Yin, Linfei & He, Xiaoyu, 2023. "Artificial emotional deep Q learning for real-time smart voltage control of cyber-physical social power systems," Energy, Elsevier, vol. 273(C).
    11. Sima, Catalina Alexandra & Popescu, Claudia Laurenta & Popescu, Mihai Octavian & Roscia, Mariacristina & Seritan, George & Panait, Cornel, 2022. "Techno-economic assessment of university energy communities with on/off microgrid," Renewable Energy, Elsevier, vol. 193(C), pages 538-553.
    12. Habiba Drias & Lydia Sonia Bendimerad & Yassine Drias, 2022. "A Three-Phase Artificial Orcas Algorithm for Continuous and Discrete Problems," International Journal of Applied Metaheuristic Computing (IJAMC), IGI Global, vol. 13(1), pages 1-20, January.
    13. Liu, Min & Qin, Jianjun & Lu, Da-Gang & Zhang, Wei-Heng & Zhu, Jiang-Sheng & Faber, Michael Havbro, 2022. "Towards resilience of offshore wind farms: A framework and application to asset integrity management," Applied Energy, Elsevier, vol. 322(C).
    14. Fan, Dongming & Ren, Yi & Feng, Qiang & Liu, Yiliu & Wang, Zili & Lin, Jing, 2021. "Restoration of smart grids: Current status, challenges, and opportunities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 143(C).
    15. Costa, Vinicius Braga Ferreira da & Bonatto, Benedito Donizeti, 2023. "Cutting-edge public policy proposal to maximize the long-term benefits of distributed energy resources," Renewable Energy, Elsevier, vol. 203(C), pages 357-372.
    16. Mohseni, Soheil & Brent, Alan C. & Kelly, Scott & Browne, Will N., 2022. "Demand response-integrated investment and operational planning of renewable and sustainable energy systems considering forecast uncertainties: A systematic review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 158(C).
    17. Younesi, Abdollah & Shayeghi, Hossein & Safari, Amin & Siano, Pierluigi, 2020. "Assessing the resilience of multi microgrid based widespread power systems against natural disasters using Monte Carlo Simulation," Energy, Elsevier, vol. 207(C).
    18. Kizito, Rodney & Liu, Zeyu & Li, Xueping & Sun, Kai, 2022. "Multi-stage stochastic optimization of islanded utility-microgrids design after natural disasters," Operations Research Perspectives, Elsevier, vol. 9(C).
    19. Gholami, M. & Sanjari, M.J., 2021. "Multiobjective energy management in battery-integrated home energy systems," Renewable Energy, Elsevier, vol. 177(C), pages 967-975.
    20. Hou, Hui & Tang, Junyi & Zhang, Zhiwei & Wang, Zhuo & Wei, Ruizeng & Wang, Lei & He, Huan & Wu, Xixiu, 2023. "Resilience enhancement of distribution network under typhoon disaster based on two-stage stochastic programming," Applied Energy, Elsevier, vol. 338(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:renene:v:200:y:2022:i:c:p:303-319. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/renewable-energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.